Skip to content
CalcGospel 國際數學圖譜
返回

IAL 2025 Jan FP1 Q2

A Level / Edexcel / FP1

IAL 2025 Jan Paper · Question 2

题目

Problem

f(x)=x27x4xx3x>0f(x) = x^2 - \frac{7x - 4\sqrt{x}}{x^3}\quad x > 0

(a) Show that the equation f(x)=0f(x) = 0 has a root α\alpha in the interval [0.3,0.4][0.3, 0.4]

(2)

(b) Determine f(x)f'(x).

(3)

(c) Using x0=0.3x_0 = 0.3 as a first approximation for α\alpha, apply the Newton–Raphson procedure once to f(x)f(x) to determine a second approximation for α\alpha, giving your answer to 3 decimal places.

(2)

The equation f(x)=0f(x) = 0 has another root β\beta in the interval [1.3,1.5][1.3, 1.5]

(d) Use linear interpolation once on the interval [1.3,1.5][1.3, 1.5] to determine an approximation for β\beta, giving your answer to 3 decimal places.

(2)
题目中文翻译

已知函数 f(x)=x27x4xx3x>0f(x) = x^2 - \frac{7x - 4\sqrt{x}}{x^3}\quad x > 0

(a) 证明方程 f(x)=0f(x) = 0 在区间 [0.3,0.4][0.3, 0.4] 内有一个根 α\alpha

(b) 求出 f(x)f'(x)

(c) 以 x0=0.3x_0 = 0.3 作为 α\alpha 的首次近似值,对 f(x)f(x) 应用一次 Newton–Raphson 迭代法以确定 α\alpha 的第二次近似值,结果保留 3 位小数。

方程 f(x)=0f(x) = 0 在区间 [1.3,1.5][1.3, 1.5] 内有另一个根 β\beta

(d) 在区间 [1.3,1.5][1.3, 1.5] 上应用一次线性插值法(linear interpolation)来确定 β\beta 的近似值,结果保留 3 位小数。

解答

(a)

解法一

思路

展开

分别计算区间两个端点处的函数值。由于 ffx>0x>0 上连续,只要两个函数值异号,便可由介值定理判断区间内存在一个根。

答题过程

展开

At the endpoints of the interval,

f(0.3)=3.456304>0f(0.3)=3.456304\ldots>0

and

f(0.4)=4.061529<0.f(0.4)=-4.061529\ldots<0.

Since ff is continuous for x>0x>0 and there is a change of sign, the equation f(x)=0f(x)=0 has a root α\alpha in the interval

[0.3,0.4].\boxed{[0.3,0.4]}.

(b)

解法一

思路

展开

先把分式改写为幂函数之和,再逐项求导。这样可以直接使用幂函数求导法则,减少使用商法则时的代数运算。

答题过程

展开

First rewrite f(x)f(x) using indices:

f(x)=x27x4xx3=x27x2+4x52.\begin{align*} f(x) =&\,x^2-\frac{7x-4\sqrt{x}}{x^3}\\ =&\,x^2-7x^{-2}+4x^{-\frac52}. \end{align*}

Therefore,

f(x)=2x+14x310x72.\begin{align*} f'(x) =&\,2x+14x^{-3}-10x^{-\frac72}. \end{align*}

Hence,

f(x)=2x+14x310x72.\boxed{f'(x)=2x+14x^{-3}-10x^{-\frac72}}.

(c)

解法一

思路

展开

将首次近似值 x0=0.3x_0=0.3 代入 Newton–Raphson 公式 xn+1=xnf(xn)f(xn)x_{n+1}=x_n-\frac{f(x_n)}{f'(x_n)},只迭代一次并将结果保留 3 位小数。

答题过程

展开

Using the Newton–Raphson formula

xn+1=xnf(xn)f(xn),x_{n+1}=x_n-\frac{f(x_n)}{f'(x_n)},

with x0=0.3x_0=0.3, we have

f(0.3)=3.456304815f(0.3)=3.456304815\ldots

and

f(0.3)=157.0821698.f'(0.3)=-157.0821698\ldots.

Thus

x1=0.33.456304815157.0821698=0.322003164.\begin{align*} x_1 =&\,0.3-\frac{3.456304815\ldots}{-157.0821698\ldots}\\ =&\,0.322003164\ldots. \end{align*}

Therefore, to 3 decimal places,

α0.322.\boxed{\alpha\approx0.322}.

(d)

解法一

思路

展开

先求 f(1.3)f(1.3)f(1.5)f(1.5),再用连接两端点的直线与 xx 轴的交点作为根的线性插值近似值。

答题过程

展开

At the endpoints,

f(1.3)=0.3761348655f(1.3)=-0.3761348655\ldots

and

f(1.5)=0.5904383661.f(1.5)=0.5904383661\ldots.

Using linear interpolation,

β=1.3f(1.5)1.5f(1.3)f(1.5)f(1.3)=1.3(0.5904383661)1.5(0.3761348655)0.5904383661(0.3761348655)=1.377828529.\begin{align*} \beta =&\,\frac{1.3f(1.5)-1.5f(1.3)}{f(1.5)-f(1.3)}\\ =&\,\frac{1.3(0.5904383661\ldots)-1.5(-0.3761348655\ldots)} {0.5904383661\ldots-(-0.3761348655\ldots)}\\ =&\,1.377828529\ldots. \end{align*}

Therefore, to 3 decimal places,

β1.378.\boxed{\beta\approx1.378}.